Interference is one of the factors that may impair the performance of a wireless communication network. Interference reduces the capacity of a wireless communication channel and causes problems such as dropped calls, reduced data rates, etc.
It is common for wireless communication network designers to develop a method to mitigate interference. The most commonly used approaches include underutilizing communication channels, limiting the number of users in a communication network, and reducing the coverage area of a cell. In essence, conventional methods trade spectrum efficiency for better performance of a wireless communication network. As a result, it takes longer for a wireless communication network service provider to recover the investment in a wireless communication network.
In a wireless communication network, a base transceiver station (BTS) equipped with an antenna array has the facility to shape its antenna beam pattern. By applying a set of beamforming weighting vectors to the antenna array, the BTS can create a directional beam steered toward a specific customer premises equipment (CPE) to increase the strength of a signal.
The same technique can be adopted to mitigate interference in a wireless communication network. The nulling angle of an antenna beam pattern could be placed toward the interference direction of arrival (DOA), while most of the gain on the beam is still maintained in the direction of the CPE. As a result, the strength of an interference signal is diminished to the point that it has less or no effect on the wireless communication network. This approach is commonly known as interference nulling for antenna arrays.
In a wireless communication network that employs interference nulling for antenna arrays, a beamforming weighting vector w of an antenna array is determined based on the following eigenvalue equation: (Ri+σn2I)−1Rs·w=λw (1), where Ri is the covariance matrix calculated from interference signals; σn is the standard deviation of channel noises; Rs is the covariance matrix calculated from the desired signals; I is the identity matrix; λ is the maximum eigenvalue. This is often referred to as an eigenvalue beamforming/interference suppression method.
The interference covariance matrix in equation 1 describes interference DOA. Since the beamforming weighting vector calculated from equation 1 takes the interference DOA into consideration, the antenna beam pattern is rotated properly. In other words, by applying the beamforming weighting vector to the antenna array on the BTS, the antenna beam pattern is rotated, with the nulling angle repositioned toward the interference DOA. Conventionally, an interference covariance matrix is determined by the spatial signatures of interference signals.
FIG. 1 is a diagram that depicts an antenna beam pattern and interference DOA in an ideal environment. A dominant beam 110 is shown as a lobe in the antenna beam pattern. Signal DOA 120 and interference DOA 130 are shown as a straight line. A nulling angle 140 is positioned toward the interference DOA 130. Since the interference DOA 130 falls within the nulling angle 140, the strength of the interference signal is greatly reduced. As illustrated in FIG. 1, the null is located at the very steep slope of an antenna beam pattern.
FIG. 2A is a diagram that depicts an antenna beam pattern and interference DOA in an actual environment. Interference DOA 220 falls within a dominant beam 210 of the antenna beam pattern. As a result, interference signals reduce the signal to noise ratio of the CPE.
FIG. 2B is a diagram that depicts an antenna beam pattern with conventional interference nulling of antenna arrays. It shows a scenario in which interference DOA 220 remains within a dominant beam 212 after the antenna beam pattern is rotated by a rotation angle 240. A small degree of error in the interference covariance matrix reduces the accuracy of the beamforming weighting vector, which in turn leads to an incorrect rotation angle so that the nulling angle misses the interference DOA. In this scenario, the performance of the wireless communication network is degraded.
As such, what is desired is a method and system for improving an interference covariance matrix, used in an interference nulling method, which will produce a more effective beamforming weighting vector that yields a wider nulling angle. A wider nulling angle makes an antenna beam pattern less susceptible to an error in the interference covariance matrix.